Product Updates
Check out the latest and greatest of our product updates including feature updates, updates to our product strategy, and deep dives into existing product capabilities.
January 16th, 2020
Integrated Version Control: Linking Rasa X with Git-based Development Workflows
Rasa
As of Rasa X version 0.23.0, we’ve added a new feature that allows developers to version training data by connecting Rasa X with a Git repository on a remote server.
December 17th, 2019
Rasa Open Source + Rasa X: Better Together
Rasa
We recently launched Rasa X, a free toolset that helps you quickly iterate on and improve the quality of your contextual assistant built using Rasa Open Source.
December 2nd, 2019
NLP vs. NLU: What's the Difference and Why Does it Matter?
Rasa
The terms NLP and NLU are often used interchangeably, but they have slightly different meanings. Learn the difference between natural language processing and natural language understanding and why they're important for successful conversational applications.
November 26th, 2019
You May Not Need to Fine-tune: ConveRT Featurizer Makes Sentence Representations More Efficient
Daksh Varshneya
Introducing a new featurizer based on a recently proposed sentence encoding model, ConveRT. We explain how you can use it in Rasa to get very strong performance with a model that trains in minutes on a CPU.
September 24th, 2019
Introducing Rasa X 0.21: Bringing Key Features of Rasa into Rasa X
Ty Dunn
Rasa X 0.21 includes improved support for the things you love in Rasa as well as updates to the features you already use in Rasa X.
September 12th, 2019
Integrate response retrieval models in assistants built with Rasa
Daksh Varshneya
Do you want to handle a lot of FAQ, chitchat and other single-turn interactions within your assistant built with Rasa? With Rasa 1.3.0 released, it’s easier than ever. Check out the blogpost to find out how.
September 5th, 2019
Pruning BERT to accelerate inference
Samuel Sučík
After previously discussing various ways of accelerating models like BERT, in this blog post we empirically evaluate the pruning approach.…
August 8th, 2019
Compressing BERT for faster prediction
Samuel Sučík
Let's look at compression methods for neural networks, such as quantization and pruning. Then, we apply one to BERT using TensorFlow Lite.
May 21st, 2019
Algorithms alone won’t solve conversational AI - Introducing Rasa X
Alan Nichol
We're excited to announce Rasa X, our new product for developers in early access. Also, our open source framework Rasa is now available in 1.0
May 21st, 2019
Rasa X: Getting started as a current Rasa user
Justina Petraitytė
Rasa X is a tool designed to make it easier to deploy and improve Rasa-powered assistants by learning from real conversations. Learn how you can use it to take your Rasa assistant to the whole new level.
February 27th, 2019
How to build HIPAA compliant AI Assistants using Rasa
Dominik Rosenkranz
TL;DR: Rasa provides a way to develop your HIPAA compliant conversational AI Assistants. It gives you the full functionality and…
February 19th, 2019
Enhancing Rasa NLU models with Custom Components
Justina Petraitytė
In this tutorial, you'll learn how to create custom components and add them to the Rasa NLU pipeline to take your AI assistants to a whole new level.
November 29th, 2018
Attention, Dialogue, and Learning Reusable Patterns
Alan Nichol
Our latest research paper introduces the new embedding policy (REDP), which is much better at dealing with uncooperative users than our standard LSTM.
September 13th, 2018
Improving Entity Extraction with Lookup Tables
Tyler Hughes
Extracting meaning from text is at the core of any NLU system. Rasa NLU + Lookup tables can dramatically improve entity extraction for your application.
April 18th, 2018
Supervised Word Vectors from Scratch in Rasa NLU
Alan Nichol
We’ve released a new pipeline, Rasa NLU 0.12 which uses very little memory, handles hierarchical intents, messages containing multiple intents, and has fewer out-of-vocabulary issues.